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Zhe Bai
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Cited by
Year
Dynamic mode decomposition for compressive system identification
Z Bai, E Kaiser, JL Proctor, JN Kutz, SL Brunton
AIAA Journal 58 (2), 561-574, 2020
1072020
Low-dimensional approach for reconstruction of airfoil data via compressive sensing
Z Bai, T Wimalajeewa, Z Berger, G Wang, M Glauser, PK Varshney
AIAA journal 53 (4), 920-933, 2015
892015
Data-driven methods in fluid dynamics: Sparse classification from experimental data
Z Bai, SL Brunton, BW Brunton, JN Kutz, E Kaiser, A Spohn, BR Noack
Whither turbulence and big data in the 21st century?, 323-342, 2017
562017
Non-intrusive Nonlinear Model Reduction via Machine Learning Approximations to Low-dimensional Operators
Z Bai, L Peng
Adv. Model. and Simul. in Eng. Sci. 8 (1), 28, 2021
152021
Randomized methods to characterize large-scale vortical flow networks
Z Bai, NB Erichson, M Gopalakrishnan Meena, K Taira, SL Brunton
PloS one 14 (11), e0225265, 2019
132019
Towards fast and accurate predictions of radio frequency power deposition and current profile via data-driven modelling: applications to lower hybrid current drive
GM Wallace, Z Bai, R Sadre, T Perciano, N Bertelli, S Shiraiwa, EW Bethel, ...
Journal of Plasma Physics 88 (4), 895880401, 2022
122022
Physics based compressive sensing approach applied to airfoil data collection and analysis. AIAA Paper 2013-0772
Z Bai, T Wimalajeewa, Z Berger, G Wang, M Glauser, PK Varshney
51st Aerospace Sciences Meeting, 2013
8*2013
Physics based compressive sensing approach applied to airfoil data collection and analysis
Z Bai, T Wimalajeewa, ZP Berger, G Wang, M Glauser, PK Varshney
51st AIAA Aerospace Sciences Meeting including the New Horizons Forum and …, 2013
72013
Adaptable Deep Learning and Probabilistic Graphical Model System for Semantic Segmentation
M Avaylon, R Sadre, Z Bai, T Perciano
Advances in Artificial Intelligence and Machine Learning 2 (01), 288-302, 2022
22022
FTL: Transfer Learning Nonlinear Plasma Dynamic Transitions in Low Dimensional Embeddings via Deep Neural Networks
Z Bai, X Wei, W Tang, L Oliker, Z Lin, S Williams
arXiv preprint arXiv:2404.17466, 2024
12024
Towards fast, accurate predictions of RF simulations via data-driven modeling: Forward and lateral models
GM Wallace, Z Bai, N Bertelli, EW Bethel, T Perciano, S Shiraiwa, ...
AIP Conference Proceedings 2984 (1), 2023
12023
On the development of robust real-time capable ICRF modeling via machine learning
Á Sánchez Villar, Z Bai, N Bertelli, EW Bethel, J Hillairet, T Perciano, ...
Bulletin of the American Physical Society, 2024
2024
Real-time capable modeling of ICRF heating on NSTX and WEST via machine learning approaches
Á Sánchez-Villar, Z Bai, N Bertelli, EW Bethel, J Hillairet, T Perciano, ...
Nuclear Fusion 64 (9), 096039, 2024
2024
FTL: Transfer Learning Nonlinear Plasma Dynamic Transitions in Low Dimensional Embeddings (FTL) v1. 0
Z Bai, L Oliker, S Williams
Lawrence Berkeley National Laboratory (LBNL), Berkeley, CA (United States), 2024
2024
AutoCT: Automated CT registration, segmentation, and quantification
Z Bai, A Essiari, T Perciano, KE Bouchard
SoftwareX 26, 101673, 2024
2024
Data for" Real-time capable modeling of ICRF heating on NSTX and WEST via machine learning approaches"
Á Sánchez-Villar, Z Bai, N Bertelli, EW Bethel, J Hillairet, T Perciano, ...
Princeton Plasma Physics Laboratory (PPPL), Princeton, NJ (United States), 2024
2024
Overview and findings of the FES Scientific Machine Learning project," Accelerating radio frequency modeling using machine learning"
J Wright, Z Bai, G Wallace, N Bertelli, T Perciano, S Shiraiwa, ...
Bulletin of the American Physical Society, 2023
2023
ICRF wave propagation and absorption modelling via machine learning
Z Bai, N Bertelli, EW Bethel, T Perciano, S Shiraiwa, G Wallace, JC Wright
2023
Methodology for surrogate modeling implementation: application to the ICRF wave absorption forward problem
Á Sánchez Villar, Z Bai, N Bertelli, EW Bethel, J Hillairet, T Perciano, ...
APS Division of Plasma Physics Meeting Abstracts 2023, BO05. 015, 2023
2023
Development of surrogate models for the TORIC ICRF spectrum solver using ML algorithms
Á Sánchez Villar, Z Bai, N Bertelli, EW Bethel, J Hillairet, T Perciano, ...
APS Division of Plasma Physics Meeting Abstracts 2023, NP11. 048, 2023
2023
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